Ethical AI Integration in Cybersecurity Operations: A Framework for Bias Mitigation and Human Oversight in Security Decision Systems

Abstract

Concerns about algorithmic fairness, transparency, and supervision are at the forefront of new AI ethical dilemmas, which are affecting cybersecurity in particular. Incorporating human-centered design, accountability, and fairness into security decision-making processes, this study presents a mitigated framework for ethical AI inclusion. The study lays out the primary mechanisms for oversight, including explainable AI interfaces, continuous feedback units, Human-in-the-Loop (HITL) and Human-on-the-Loop (HOTL) oversight, and technical case studies and normative models. The findings highlight the most crucial areas for future study and cross-disciplinary collaboration in cybersecurity, while also demonstrating the possibilities and limitations of ethically deploying AI.